In　this　study,　based　on　the　National　Centers　for　Environmental　Prediction　(NCEP)　Final　Analysis　(FNL)　data,　the　reliability　and　performances　of　their　application　on　clean　days　and　polluted　days　(based　on　the　PM2.5　mass　concentrations)　in　Beijing　were　assessed.　Conventional　meteorological　factors　and　diagnostic　physical　quantities　from　the　NCEP/FNL　data　were　compared　with　the　L-band　radar　observations　in　Beijing　in　the　autumns　and　winters　of　2017-2019.　The　results　indicate　that　the　prediction　reliability　of　the　temperature　was　the　best　compared　with　those　of　the　relative　humidity　and　wind　speed.　It　is　worth　noting　that　the　relative　humidity　was　lower　and　the　near-surface　wind　speed　was　higher　on　polluted　days　from　the　NCEP/FNL　data　than　from　the　observations.　As　far　as　diagnostic　physical　quantity　is　concerned,　it　was　revealed　that　the　temperature　inversion　intensity　depicted　by　the　NCEP/FNL　data　was　significantly　lower　than　that　from　the　observations,　especially　on　polluted　days.　For　example,　the　difference　in　the　temperature　inversion　intensity　between　the　NCEP/FNL　data　and　the　observation　ranged　from　-0.56　to　-0.77　degrees　C　on　polluted　days.　In　addition,　the　difference　in　the　wind　shears　between　the　NCEP/FNL　reanalysis　data　and　the　observations　increased　to　0.40　m/s　in　the　lower　boundary　layer　on　polluted　days　compared　with　that　on　clean　days.　Therefore,　it　is　suggested　that　the　underestimation　of　the　relative　humidity　and　temperature　inversion　intensity,　and　the　overestimation　of　the　near-surface　wind　speed　should　be　seriously　considered　in　simulating　the　air　quality　in　the　model,　particularly　on　polluted　days,　which　should　be　focused　on　more　in　future　model　developments.